Corrosion induced failure analysis of subsea pipelines

Yang, Yongsheng; Khan, Faisal; Thodi, Premkumar; Abbassi, Rouzbeh

doi:10.1016/j.ress.2016.11.014

Cited by 148 publications

(30 citation statements)

References 16 publications

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“…Moreover, Chen and Wu [35] employed FMECA to determine, classify, and analyze common failures in the municipal solid waste lifecycle, and the findings could be used to minimize potential failures and bring continuous improvement. Yang et al [36] established an object-oriented Bayesian network (OOBN) model to analyze the observed abnormal events to evaluate the running status of the subsea pipeline. e estimated failure probabilities are important basis of failure control.…”

Section: Failure Analysismentioning

confidence: 99%

Analysis of Failures and Influence Factors of Critical Infrastructures: A Case of Metro

Deng

Song

Zhou

et al. 2020

Advances in Civil Engineering

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Metro plays an indispensable role in promoting social and economic development of the big cities. However, the safety operation of the metro system is believed to be an arduous work for its operation being susceptible to various factors, especially equipment failure, which could bring about delay, interruption, and even accidents. In consideration of the seriousness of metro accident, it is becoming more and more crucial to conduct proactive, targeted, and effective risk management to reduce failures. Firstly, based on the FMECA and influence diagram theory, this paper proposes a new analytical framework to study metro equipment failure in accordance with system decomposition. Furthermore, a case study is implemented to verify the feasibility and availability of this framework in evaluating criticality of failure modes and assessing its influence factors based on the collected data from metro operation company. As indicated by the research results, wheel damage is the most serious failure mode in the bogie system, and its most paramount influence factor is the shortage of professional skills. Finally, a discussion about the research methods and results is carried out, and several recommendations are put forward to improve safety management on the basis of research findings. This study has the potential to offer suggestions in regard to metro equipment design, operation, and maintenance for raising the safety level in metro operation.

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Section: Failure Analysismentioning

confidence: 99%

Analysis of Failures and Influence Factors of Critical Infrastructures: A Case of Metro

Deng

Song

Zhou

et al. 2020

Advances in Civil Engineering

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show abstract

“…In the oil and gas industry, the underground and subsea pipelines are more prone to general corrosion, fatigue, stress cracking and pitting [ 101 ]. Most of the times, these huge pipe networks carry petroleum fluids at high pressure/temperature and are exposed to extreme environmental sea conditions from the external side [ 102 , 103 ].…”

Section: Research Literature Review On Various Aspects Of Ugws Tecmentioning

confidence: 99%

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves

Abbas

Shafiee

2018

Sensors

113

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Ultrasonic guided wave (UGW) is one of the most commonly used technologies for non-destructive evaluation (NDE) and structural health monitoring (SHM) of structural components. Because of its excellent long-range diagnostic capability, this method is effective in detecting cracks, material loss, and fatigue-based defects in isotropic and anisotropic structures. The shape and orientation of structural defects are critical parameters during the investigation of crack propagation, assessment of damage severity, and prediction of remaining useful life (RUL) of structures. These parameters become even more important in cases where the crack intensity is associated with the safety of men, environment, and material, such as ship’s hull, aero-structures, rail tracks and subsea pipelines. This paper reviews the research literature on UGWs and their application in defect diagnosis and health monitoring of metallic structures. It has been observed that no significant research work has been convened to identify the shape and orientation of defects in plate-like structures. We also propose an experimental research work assisted by numerical simulations to investigate the response of UGWs upon interaction with cracks in different shapes and orientations. A framework for an empirical model may be considered to determine these structural flaws.

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“…It is specified as the gradual reduction in the pipeline wall thickness that might lead to substantial environmental and economic consequences as a result of catastrophic events, including leaks and ruptures. Therefore, pipeline integrity management has become highly essential [ 1 ]. Pipeline integrity management is composed of the pipelines’ inspection, repair, and maintenance with the scope of preventing failures and ensuring the safety of the pipelines during their lifecycles [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Condition-Based Maintenance with Reinforcement Learning for Dry Gas Pipeline Subject to Internal Corrosion

Mahmoodzadeh

Droguett

et al. 2020

Sensors

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Gas pipeline systems are one of the largest energy infrastructures in the world and are known to be very efficient and reliable. However, this does not mean they are prone to no risk. Corrosion is a significant problem in gas pipelines that imposes large risks such as ruptures and leakage to the environment and the pipeline system. Therefore, various maintenance actions are performed routinely to ensure the integrity of the pipelines. The costs of the corrosion-related maintenance actions are a significant portion of the pipeline’s operation and maintenance costs, and minimizing this large cost is a highly compelling subject that has been addressed by many studies. In this paper, we investigate the benefits of applying reinforcement learning (RL) techniques to the corrosion-related maintenance management of dry gas pipelines. We first address the rising need for a simulated testbed by proposing a test bench that models corrosion degradation while interacting with the maintenance decision-maker within the RL environment. Second, we propose a condition-based maintenance management approach that leverages a data-driven RL decision-making methodology. An RL maintenance scheduler is applied to the proposed test bench, and the results show that applying the proposed condition-based maintenance management technique can reduce up to 58% of the maintenance costs compared to a periodic maintenance policy while securing pipeline reliability.

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Corrosion induced failure analysis of subsea pipelines

Cited by 148 publications

References 16 publications

Analysis of Failures and Influence Factors of Critical Infrastructures: A Case of Metro

Analysis of Failures and Influence Factors of Critical Infrastructures: A Case of Metro

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves

Condition-Based Maintenance with Reinforcement Learning for Dry Gas Pipeline Subject to Internal Corrosion

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